Calculate the bias between a reference and target dataset.
Calculate the bias between a reference and target dataset.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | The difference between the reference and target datasets. |
Return type: |
Abstract Base Class from which all binary metrics inherit.
Run the metric for the given reference and target datasets.
Parameters: |
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Returns: | The result of evaluation the metric on the reference and target dataset. |
Base Metric Class
Calculate the correlation coefficient between two datasets
Calculate the correlation coefficient between two dataset.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | The correlation coefficient between a reference and target dataset. |
Calculate the Root Mean Square Difference (RMS Error), with the mean calculated over time and space.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | The RMS error, with the mean calculated over time and space |
Calculate the target to reference ratio of spatial standard deviation and pattern correlation
Calculate two metrics to plot a Taylor diagram to compare spatial patterns
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | standard deviation ratio, pattern correlation coefficient |
Return type: | :float:’float’,’float’ |
Calculate the standard deviation ratio between two datasets.
Calculate the standard deviation ratio.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | The standard deviation ratio of the reference and target |
Calculate the temporal correlation coefficients and associated confidence levels between two datasets, using Pearson’s correlation.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | A 2D array of temporal correlation coefficients and a 2D array of confidence levels associated with the temporal correlation coefficients |
Calculate the bias averaged over time.
Calculate the bias averaged over time.
Note
Overrides BinaryMetric.run()
Parameters: |
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Returns: | The mean bias between a reference and target dataset over time. |
Calculate the standard deviation over the time.
Calculate the temporal std. dev. for a datasets.
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Overrides UnaryMetric.run()
Parameters: | target_dataset (dataset.Dataset) – The target_dataset on which to calculate the temporal standard deviation. |
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Returns: | The temporal standard deviation of the target dataset |
Return type: | ndarray |
Abstract Base Class from which all unary metrics inherit.
Run the metric for a given target dataset.
Parameters: | target_dataset (dataset.Dataset) – The dataset on which the current metric will be run. |
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Returns: | The result of evaluating the metric on the target_dataset. |
Calculate difference between two arrays
Parameters: |
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Returns: | Biases array of the target dataset |
Return type: | :class:’numpy.ma.core.MaskedArray’ |
Calculate the correlation coefficient between two arrays.
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Returns: | pearson’s correlation coefficient between the two input arrays |
Return type: | :class:’numpy.ma.core.MaskedArray’ |
Calculate ratio of standard deivations of the two arrays
Parameters: |
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Returns: | root mean square error |
Return type: | :class:’float’ |
Calculate a sample standard deviation of an array along the array
Parameters: |
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Returns: | sample standard deviation of array |
Return type: | :class:’numpy.ma.core.MaskedArray’ |
Calculate ratio of standard deivations of the two arrays
Parameters: |
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Returns: | (standard deviation of target_array)/(standard deviation of reference array) |
Return type: | :class:’float’ |